1. Technical Field of the Invention
The present invention generally relates to interaction of a user with a personal computer, and more particularly to a method and system for launching applications (e.g., e-mail client) and accessing data associated therewith (e.g., e-mail) by identifying a user via a digital camera, utilizing an edge-detection algorithm.
2. Description of the Related Art
People interface with other people by words and vocal inflections, by subtle bodily movements and nuances of gaze, by touch and gesture, and even by uncontrollable reactions like blushing or falling speechless. In contrast, people interface with personal computers via two primary interfaces: a keyboard and a pointing device (e.g., a mouse). However, the primary interfaces often provide for tedious, even sometimes difficult and time-consuming interaction between people and personal computers. Furthermore, although personal computers have become less expensive and yet more powerful, they still remain difficult to use.
A personal computer's icon-oriented desktop and user interfaces coupled with primary interfaces described above have changed little in the last several decades. Attempts to make personal computers easier to use have focused around the foregoing desktop, user interfaces and primary interfaces. For the most part, developers have concentrated on making personal computers easier to use by changing the foregoing interfaces (i.e., both user interfaces and primary interfaces) rather than changing an entire paradigm for interfacing people (i.e., users) with personal computers. In other words, developers have tried the make the foregoing interfaces provide better and easier interactivity between users and personal computer, but have failed to look “outside the box” for alternative methods of user interaction with personal computers.
However, alternative methods of user interaction with personal computers have been attempted. Some developers have examined using infrared motion sensors to identify movement of a person in proximity to a personal computer, and more specifically, have examined a rate of such movement (slew rate). Other developers have examined using a human emotion as input to a personal computer by utilizing visual techniques that analyze facial expressions, where the computer can be programmed to provide correct responses to queries or even provide prompts or proactive conversation with the user based on the use's emotional states. For example, if the user is determined to be depressed, the personal computer could ask, “What's wrong?” or even discuss the determined problem. Still other developers have examined using retinal imaging and position of a pupil in a human eye to guide a pointing device or a text cursor by following a movement of the eye.
Still further, biometrics has been a burgeoning field directed to studying measurable biological and physiological characteristics of a person. In computer technology, biometrics has been used for authentication techniques that rely on measurable biological and physiological characteristics that can automatically be checked or verified by a computer. More particularly, biometrics has been used for fingerprint identification, retinal and hand scanning, face and voice recognition, and the like. Computer technology implementing biometric devices (e.g., particularly for facial recognition) has focused upon nearly exact identification (i.e., small margin of error) of a person from within a very large group or population, using sophisticated highly priced equipment and algorithms. Such sophistication and expense are warranted for use in security, law enforcement, and corporate identification systems. That is, the technology implementing biometric devices necessarily requires highly priced equipment capable of exact measurements within a very small margin of error, which in turn require complex algorithms, tremendous computing power, and proprietary software development for the algorithms.
Conventional computer technology for determining an identity of a computer user for accessing e-mail and launching applications requires a personal computer to provide some form of rudimentary authentication using a logon mechanism, which generally consists of a username and a password. As described above, computer technology implementing biometric devices for facial recognition has focused upon a nearly exact identification of a person from within a very large population, thereby requiring sophisticated high-priced equipment and algorithms. The algorithms used by this equipment (e.g., video or photographic imaging and thermography) require powerful machines, with fast processors and substantial amount of memory (e.g., both volatile and non-volatile). The foregoing sophisticated and costly technology is cost-prohibitive for low-cost computing devices (e.g., Internet appliances), desktop and notebook personal computers. Additionally, the foregoing hardware requirements prevent such sophisticated equipment from being used on smaller and less-powerful computing devices (e.g., Internet appliance), and low-cost desktop and notebook personal computers.
Edge detection algorithms are known in the art and are generally used for: 1) detecting or identifying parts or components on a conveyor belt; 2) identifying or selecting elements or objects from certain types of backgrounds; and/or 3) converging multiple images into a mosaic image. Edge detection is generally grouped into two categories: 1) gradient filter (e.g., Sobel filter); and 2) Laplacian filter (and/or Gaussian filter). One skilled in the art will readily appreciate that the gradient filter detects edges by identifying intensities in first-order derivatives in horizontal and vertical directions (i.e., X, Y directions) of an image, while the Laplacian filter detects edges by identifying zero crossings in second-order derivatives of the image. Additionally, one skilled in the art understands that the Laplacian filter is more sensitive than the Sobel filter for identifying edges, but is more sensitive to noise. One skilled in the art with readily appreciate that heretofore the foregoing algorithms have not been used in a computing device for launching applications (e.g., e-mail client) and accessing data associated therewith (e.g., e-mail) by determining an identity of a computer user based on the edge detection algorithms.
Considering the foregoing, it is very desirable to provide a method and system for determining the identity of the computer user for launching applications and accessing data associated therewith (e.g., launching e-mail client and retrieving e-mail associated therewith) via a digital camera, using an edge-detection algorithm, such that the method and system are not cost-prohibitive and can easily and cost-effectively be employed in an computing device (e.g., Internet device) having the ability to easily differentiate among household members or members of a small-sized organization (i.e., users).